A key element in any pore pressure prediction study is the comparison between the predicted pore pressure at the prospect location and the formation pressure measurements in offset wells. In order to understand, and predict, pressure distribution within a basin, pressure data and the sediments within which pressure regimes are confined need to be analyzed within a robust and consistent stratigraphic framework. This comparison is primarily required for: a) calibration for forward modelling and b) to have an idea of the extremes in the various pore pressure scenarios in a particular basin. The formation pressure measurements are acquired in permeable units like sands and are assumed to be in pressure equilibrium with adjacent shales. Thus, the predicted estimates in shales are compared with pore pressure measurements from sands in offset wells. This comparison is imprecise until and unless the offset pressure measurement is normalized to the same frame of reference at the prospect. The normalization process of offset pressure data can be broadly classified into two types: a) the simplistic depth normalization and b) the more detailed stratigraphic normalization. The simplistic depth normalization involves mere normalization of offset pressure measurements with respect to change in the positioning of the datum reference in the prospect location; this method precludes consideration of the structural difference (current plumbing) of each geological unit or in-depth analyses of depositional setup in offset and prospect locations presuming connected sands with constant overpressure. The second method entails the understanding of the regional stratigraphy, the structural differences in positioning of each stratigraphic unit in the prospect location and offset wells, depositional setting including sand connectivity and overpressure-generating mechanisms. This method can be invoked through appropriate approaches; a) constant overpressure (OP) method, b) constant vertical effective stress (VES) method and c) ratio method (ratio of either constant OP or VES to the normal effective stress i.e. NES). Stratigraphic normalization also includes the correct positioning of the offset pressure data in each stratigraphic unit at the prospect. Whilst the above normalization methods are extremely useful concepts, they form only part of the geological definition of the pressure system for predicting pore pressure profiles in an undrilled prospect. On the basis of geological understanding, stratigraphic normalization method may be preferred over the simplistic depth normalization method. An optimized normalization process for offset well data integrated with predicted pore pressure estimates at prospect locations illustrates a realistic scenario in terms of bounds of uncertainty. This paper brings forth a new dimension in predicting pore pressures at new prospects by describing scenarios within the framework of the conceived geological model. Also, the methods discussed provide the scope of capturing a valid uncertainty envelope that is imperative for a robust well design to define possible risks and foresee mitigation measures.
Pore pressure prediction work is typically calibrated with pressure measurements from sands and log data from the adjoining shales. This is done because compaction effects on standard well logs are better preserved in shales than in sands. The prediction work assumes that sands and adjacent shales attain pressure equilibrium over geological time. To avoid lithologic effects on rock properties, calibration requires picking of similar shales from log data. Most commonly, clean end-member shales are picked. This paper addresses the issues encountered while picking shales for real-time pore pressure prediction (RTPPP) and the strategies to deal with these issues to confirm that changes in log measurements are related to variations in shale porosity and hence pore pressure.Various shale picking issues that could impact RTPPP are: a) inconsistency in shale picking approach during model building phase and RT monitoring; b) lithology effects from presence of silt, carbonates, gas silts and organic rich shales; c) RT data issues related to logging while drilling (LWD) tool calibration and differences between phase shift and attenuation resistivity; and, d) anomalous log response like low gamma ray and low resistivity shales.The strategies adopted to mitigate these potential issues are: a) use of consistent shale picking strategy in model building and RT monitoring phases; b) application of effective media models like HashinShtrikman lower bound inversion and linear clay-volume modulation for silt correction and use of cross-plots to delineate the gas silts, etc., c) appropriate choice of resistivity tool and log curves to provide best measures of formation properties for each hole section and; d) validation of shale picks with well behavior, cuttings data and geological interpretation.An optimized shale picking strategy integrated with well behaviour is imperative for predicting pore pressures within realistic bounds of uncertainty and for avoiding under/over prediction of pore pressures that in turn jeopardizes safe drilling.
Prediction methods for pore pressure (PP) and fracture gradient (FG) developed for conventional resources include the use of normal compaction trends derived from correlations of log-based porosity with vertical effective stress (VES) and translation of pressures from offset wells to prospect locations using fluid densities and contacts. These techniques are less effective in unconventional plays like tight sands and shales because of disconnected fluids and difficulties in distinguishing PP from gas effects on the shale resistivity and compressional sonic velocities typically used for determining porosity. Unconventional resources require alternative prediction techniques such as pressure cell models, in which individual formation layers exhibit either constant overpressure (OP, difference between PP and hydrostatic pressure) or constant VES (difference between overburden stress and PP). Direct measurements from pressure gauges or estimated pressures from drilling indicators such as connection gases and kicks are used to calibrate the amount of OP or VES for each layer or pressure cell. The modeled pressures are translated to specific well locations by adjusting for differences in stratigraphic depth following either constant OP (typical for permeable formations) or constant VES (for tight formations). Fracture gradients are calculated from the PP forecasts based on horizontal-to-vertical effective stress ratios (ESRs) calibrated against total horizontal stresses determined from field data such as leak-off tests and drilling losses. Pressure cell models developed for the Sichuan Basin and evaluated against subsequent drilling experience indicate that: (1) consideration of all available offset data in combination with local geology is required to determine whether constant OP or constant VES is appropriate for each formation layer; (2) pressure-cell values can vary with both depth and area; (3) different ESRs are required for different lithologies and for depleted versus virgin pressures; and (4) all available field data (not only the nearest offset well) needs to be considered to provide realistic lower and upper bounds on PP and FG. The pressure-cell techniques described here can be calibrated with local field data and applied to unconventional resources worldwide to provide an effective method for predicting PP and FG in environments where conventional PP-FG prediction methods break down. Introduction Prediction methods for pore pressure (PP) and fracture gradient (FG) developed for conventional resources include the use of normal compaction trends derived from correlations of log-based porosity with vertical effective stress (VES) and translation of pressures from offset wells to prospect locations using fluid densities and contacts (Bowers 1995; Purkayastha et al. 2014). These techniques are less effective in unconventional plays like tight sands and shales because of disconnected fluids and difficulties in distinguishing PP from gas effects on the shale resistivity and compressional sonic velocities typically used for determining porosity (Couzens-Schultz et al. 2013).
Drill cuttings are a valuable source of information about lithology and wellbore condition. Although an abnormally high number of cuttings would indicate some sort of failure at the wellbore wall, a detailed analysis of cuttings can help to identify the type of rock failure. Cavings, fragments that are relatively larger and of different shape compared to normal cuttings, can be used to decode critical information about the wellbore geometry and formation pressure. Cuttings analysis is most useful in absence of direct indicators of wellbore condition such as caliper, image logs, or logging-while-drilling (LWD) data, but even in presence of such data, cuttings analysis can be used to corroborate the interpretations with direct measurements. Several mechanisms, such as underbalanced drilling, pre-existing weak planes, stress relief, or even the drilling process itself, can lead to production of cavings. Examining the cavings to interpret wellbore instability and mechanisms responsible for it is an expert's job and requires a good overall understanding of the prevailing geology, geomechanical principles, drilling procedure, and drilling tools. Identification of wellbore failure during drilling provides a better chance of immediate remedial action, even before a wireline logging program is executed. Differentiating cuttings generated by the drill bit from cavings created by the wellbore failure is not an easy and straightforward task due to a variety of bits and phenomena involved in the generation of cuttings. The first step in this analysis is to broadly define the different types of cavings based on their shape and size. Then, we move to the basic key features of these cuttings, and, finally, provide the remedial action plan for each type. Drill cuttings analysis was successfully applied to improve hole condition in real time for two wells drilled in the Western Offshore basin, India. One case study illustrates the importance of mud chemistry over the mud weight being used to drill. The second case study underscores the interpretation of shear failure as the reason for cavings from cuttings morphology analysis. In both the cases, timely intervention integrated with the identification of prevailing drilling issues in real time helped in understanding the mud system and its effects on the wellbore. The novelty of this approach lies in the deep understanding and geomechanical application of cavings in providing timely and cost-effective recommendations to optimize drillability in both the presence and the absence of LWD data. The results can be used during the well-planning stage of future wells and during drilling to improvise mud chemistry or to identify required increase in mud weight to avoid breakouts related to chemical instability or shear failure even though the pore pressure profile may not necessarily require any further increase in the mud weight.
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